Senior Forward Deployed Engineer

Job Description

Job Description

Role: Senior Forward Deployed Engineer
Location: Louisville, TN
Type: Contract
Rate: $70/hr

Key Responsibilities
Technical Leadership & Architecture
Design, build, and deploy end-to-end data integration pipelines using Palantir Foundry, including complex transforms, incremental pipelines, and multi-source data connectors
Architect and maintain the Ontology layer defining object types, link types, action types, and interfaces that model customer domains with precision and scalability
Develop and Eligible to workimize Python, SQL, and Java transforms across distributed (PySpark) and lightweight (Pandas, Polars, DuckDB) compute engines
Build and deploy TypeScript/Python Functions for server-side business logic, function-backed actions, and function-backed columns
Create and configure Workshop applications, OSDK-based custom applications, and custom widgets to deliver operational front-ends
Lead data governance implementation markings, permissions, restricted views, property security groups, and role-based access controls
Design and deploy AIP-powered workflows, including AIP Logic, AIP Agents, evaluation suites, and retrieval-augmented generation (RAG) pipelines
Deployment Strategy & Customer Engagement
Serve as the primary technical point of contact for senior customer stakeholders, translating business problems into platform solutions
Own deployment roadmaps end-to-end: scoping, architecture design, implementation, testing, and operationalization
Drive adEligible to workion by delivering high-quality, production-grade solutions that users trust and rely on daily
Navigate complex organizational dynamics, building relationships with executives, analysts, data engineers, and end users
Identify expansion opportunities by deeply understanding the customer's operational landscape and surfacing new use cases for the platform

Skills:
Team Leadership & Mentorship
Lead and mentor a team of Forward Deployed Engineers, providing technical guidance, code reviews, and architecture direction
Establish engineering best practices across the deployment: branching strategies (global and local), incremental pipeline design, testing, and CI/CD
Conduct knowledge-sharing sessions and internal trainings on Foundry capabilities, new platform features, and deployment patterns
Platform Mastery & Innovation
Stay at the forefront of Foundry platform evolution including Pipeline Builder, Code Workspaces, Model Studio, OSDK, Cipher, and streaming capabilities
Build and deploy machine learning models using Model Studio (no-code) and pro-code repositories for classification, regression, time series forecasting, and custom predictive modeling
Leverage the full data lifecycle: Data Connection Sync Datasets Transforms Ontology Applications Actions Writeback

Required Qualifications
5 years of experience in software engineering, data engineering, or technical consulting with at least 2 years on Palantir Foundry
Strong proficiency in Python (PySpark, Pandas, Polars) and SQL; experience with TypeScript is highly valued
Deep understanding of the Foundry Ontology object types, link types, action types, interfaces, and functions
Proven track record of designing and deploying production-grade data pipelines (batch and streaming) at enterprise scale
Experience building Workshop applications and/or OSDK-based applications (React/TypeScript)
Strong communication skills with the ability to engage both technical and non-technical stakeholders

Preferred Qualifications
Experience with Google Cloud Platform (Eligible to workP) Compute Engine, Cloud Functions, Cloud Storage, Dataflow, Pub/Sub, and IAM
Experience with Google BigQuery query Eligible to workimization, partitioning/clustering strategies, BigQuery ML, data warehousing patterns, and migration from legacy EDW platforms (e.g., Netezza, Teradata)
Experience with AIP (AI Platform) AIP Logic, AIP Agents, evaluation suites, and LLM-powered functions
Familiarity with machine learning workflows in Foundry: Model Studio, pro-code model authoring, batch/live inference
Experience implementing data governance frameworks markings, ABAC, restricted views, Cipher for data protection, and HIPAA-compliant data handling
Background in healthcare, kidney care, or clinical operations, revenue cycle Eligible to workimizations a plus.
Experience leading teams of 3 engineers in forward-deployed settings
Contributions to internal tooling, open-source projects, or platform evangelism